dc.contributor.author | Playford, CJ | |
dc.contributor.author | Gayle, V | |
dc.contributor.author | Connelly, R | |
dc.contributor.author | Gray, AJG | |
dc.date.accessioned | 2017-06-19T14:44:32Z | |
dc.date.issued | 2016-12-01 | |
dc.description.abstract | Powerful new social science data resources are emerging. One particularly important source is administrative data, which
were originally collected for organisational purposes but often contain information that is suitable for social science
research. In this paper we outline the concept of reproducible research in relation to micro-level administrative social
science data. Our central claim is that a planned and organised workflow is essential for high quality research using microlevel
administrative social science data. We argue that it is essential for researchers to share research code, because code
sharing enables the elements of reproducible research. First, it enables results to be duplicated and therefore allows the
accuracy and validity of analyses to be evaluated. Second, it facilitates further tests of the robustness of the original piece
of research. Drawing on insights from computer science and other disciplines that have been engaged in e-Research we
discuss and advocate the use of Git repositories to provide a useable and effective solution to research code sharing and
rendering social science research using micro-level administrative data reproducible. | en_GB |
dc.description.sponsorship | The author(s) disclosed receipt of the following financial
support for the research, authorship, and/or publication of
this article: Economic and Social Research Council for
Administrative Data Research Centre – Scotland project
under grant number [ES/L007487/1]. | en_GB |
dc.identifier.citation | DOI: 10.1177/2053951716684143 | en_GB |
dc.identifier.doi | 10.1177/2053951716684143 | |
dc.identifier.uri | http://hdl.handle.net/10871/28083 | |
dc.language.iso | en | en_GB |
dc.publisher | SAGE Publications | en_GB |
dc.rights | Creative Commons CC-BY: This article is distributed under the terms of the Creative Commons Attribution 3.0 License (http://
www.creativecommons.org/licenses/by/3.0/) which permits any use, reproduction and distribution of the work without further
permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-accessat-sage). | en_GB |
dc.subject | Big Data | en_GB |
dc.subject | administrative data | en_GB |
dc.subject | reproducibility | en_GB |
dc.subject | replication | en_GB |
dc.subject | workflow | en_GB |
dc.subject | Git | en_GB |
dc.title | Administrative social science data: The challenge of reproducible research | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2017-06-19T14:44:32Z | |
dc.identifier.issn | 2053-9517 | |
dc.description | This is the final version of the article. Available from the publisher via the DOI in this record. | en_GB |
dc.identifier.journal | Big Data and Society | en_GB |